Search ga_ls9c_ard_3 whole collection

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels. For these ARD products, this value comes from the Fmask algorithm. from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels. For these ARD products, this value comes from the Fmask algorithm. to (exclusive):

Time when dataset was created (processed) From

Time when dataset was created (processed) to (exclusive)

The raw CRS string as it appears in metadata:

One of - final|interim|nrt (near real time):

ID of a dataset type:

Ground sampling distance of the sensor’s best resolution band in metres; represents the size (or spatial resolution) of one pixel. from:

Ground sampling distance of the sensor’s best resolution band in metres; represents the size (or spatial resolution) of one pixel. to (exclusive):

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north from:

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north to (exclusive):

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon. from:

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon. to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm to (exclusive):

File format (GeoTiff, NetCDF):

GQA Circular error probable (90%) from:

GQA Circular error probable (90%) to (exclusive):

Mean of the absolute values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the absolute values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the absolute values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the absolute values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the absolute values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the absolute values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Absolute value of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Absolute value of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Absolute value of the total GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Absolute value of the total GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Absolute value of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Absolute value of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Circular error probable (90%) of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Circular error probable (90%) of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Dataset UUID:

User who indexed the dataset:

When dataset was indexed:

Label:

A Landsat Collection 1 Level-1 product identifier including the Collection processing levels, processing date, collection number, and collection tier category (e.g. ‘LE07_L1TP_098084_20210307_20210308_02_RT’) :

A Landsat scene ID including WRS path and row, year and day, ground station identifier and archive version number (e.g. ‘LC80900852021066LGN00’) :

Latitude range from:

Latitude range to (exclusive):

Longitude range from:

Longitude range to (exclusive):

Full metadata document:

Metadata type name of dataset:

ID of a metadata type:

Spatial reference code from the provider. For Landsat region_code is a scene path row: '{:03d}{:03d}.format(path,row)' For Sentinel it is MGRS code. In general it is a unique string identifier that datasets covering roughly the same spatial region share. :

Acquisition time range From

Acquisition time range to (exclusive)

Dataset URI:

Add field

First 100 results (query limit)

Time (local)	Label
2021-11-11 10:19:51	ga_ls9c_ard_3-2-1_100078_2021-11-11_final.stac-item
2021-11-16 10:22:19	ga_ls9c_ard_3-2-1_100078_2021-11-16_final.stac-item
2021-11-16 10:23:06	ga_ls9c_ard_3-2-1_100080_2021-11-16_final.stac-item
2021-12-26 10:26:58	ga_ls9c_ard_3-2-1_101080_2021-12-26_final.stac-item
2022-01-11 10:26:07	ga_ls9c_ard_3-2-1_101078_2022-01-11_final.stac-item
2022-01-11 10:26:55	ga_ls9c_ard_3-2-1_101080_2022-01-11_final.stac-item
2022-01-18 10:29:31	ga_ls9c_ard_3-2-1_102071_2022-01-18_final.stac-item
2022-01-27 10:26:57	ga_ls9c_ard_3-2-1_101080_2022-01-27_final.stac-item
2022-02-03 10:29:32	ga_ls9c_ard_3-2-1_102071_2022-02-03_final.stac-item
2022-02-12 10:26:06	ga_ls9c_ard_3-2-1_101078_2022-02-12_final.stac-item
2022-02-12 10:26:54	ga_ls9c_ard_3-2-1_101080_2022-02-12_final.stac-item
2022-02-19 10:29:25	ga_ls9c_ard_3-2-1_102071_2022-02-19_final.stac-item
2022-02-28 10:25:55	ga_ls9c_ard_3-2-1_101078_2022-02-28_final.stac-item
2022-02-28 10:26:43	ga_ls9c_ard_3-2-1_101080_2022-02-28_final.stac-item
2022-03-23 10:29:38	ga_ls9c_ard_3-2-1_102072_2022-03-23_final.stac-item
2022-04-08 10:29:35	ga_ls9c_ard_3-2-1_102072_2022-04-08_final.stac-item
2022-04-24 10:29:25	ga_ls9c_ard_3-2-1_102072_2022-04-24_final.stac-item
2022-05-03 10:26:24	ga_ls9c_ard_3-2-1_101080_2022-05-03_final.stac-item
2022-05-10 10:29:19	ga_ls9c_ard_3-2-1_102072_2022-05-10_final.stac-item
2022-05-12 10:19:20	ga_ls9c_ard_3-2-1_100078_2022-05-12_final.stac-item
2022-05-26 10:28:46	ga_ls9c_ard_3-2-1_102071_2022-05-26_final.stac-item
2022-05-28 10:19:12	ga_ls9c_ard_3-2-1_100078_2022-05-28_final.stac-item
2022-06-20 10:25:36	ga_ls9c_ard_3-2-1_101078_2022-06-20_final.stac-item
2022-06-20 10:26:24	ga_ls9c_ard_3-2-1_101080_2022-06-20_final.stac-item
2022-07-06 10:26:32	ga_ls9c_ard_3-2-1_101080_2022-07-06_final.stac-item
2022-07-13 10:29:04	ga_ls9c_ard_3-2-1_102071_2022-07-13_final.stac-item
2022-07-29 10:29:41	ga_ls9c_ard_3-2-1_102072_2022-07-29_final.stac-item
2022-08-14 10:29:27	ga_ls9c_ard_3-2-1_102071_2022-08-14_final.stac-item
2022-08-14 10:29:51	ga_ls9c_ard_3-2-1_102072_2022-08-14_final.stac-item
2022-08-23 10:26:54	ga_ls9c_ard_3-2-1_101080_2022-08-23_final.stac-item
2022-08-30 10:29:54	ga_ls9c_ard_3-2-1_102072_2022-08-30_final.stac-item
2022-09-17 10:20:48	ga_ls9c_ard_3-2-1_100080_2022-09-17_final.stac-item
2022-09-17 10:22:00	ga_ls9c_ard_3-2-1_100083_2022-09-17_final.stac-item
2022-09-24 10:27:02	ga_ls9c_ard_3-2-1_101080_2022-09-24_final.stac-item
2022-10-01 10:29:38	ga_ls9c_ard_3-2-1_102071_2022-10-01_final.stac-item
2022-10-10 10:27:04	ga_ls9c_ard_3-2-1_101080_2022-10-10_final.stac-item
2022-10-19 10:20:57	ga_ls9c_ard_3-2-1_100080_2022-10-19_final.stac-item
2022-10-26 10:27:08	ga_ls9c_ard_3-2-1_101080_2022-10-26_final.stac-item
2022-11-11 10:27:08	ga_ls9c_ard_3-2-1_101080_2022-11-11_final.stac-item
2022-11-27 10:27:07	ga_ls9c_ard_3-2-1_101080_2022-11-27_final.stac-item
2022-12-20 10:29:41	ga_ls9c_ard_3-2-1_102071_2022-12-20_final.stac-item
2023-01-05 10:29:43	ga_ls9c_ard_3-2-1_102071_2023-01-05_final.stac-item
2023-01-07 10:22:09	ga_ls9c_ard_3-2-1_100083_2023-01-07_final.stac-item
2023-01-14 10:27:05	ga_ls9c_ard_3-2-1_101080_2023-01-14_final.stac-item
2023-01-23 10:20:50	ga_ls9c_ard_3-2-1_100080_2023-01-23_final.stac-item
2023-01-23 10:22:02	ga_ls9c_ard_3-2-1_100083_2023-01-23_final.stac-item
2023-01-30 10:27:07	ga_ls9c_ard_3-2-1_101080_2023-01-30_final.stac-item
2023-02-08 10:22:12	ga_ls9c_ard_3-2-1_100083_2023-02-08_final.stac-item
2023-02-15 10:26:20	ga_ls9c_ard_3-2-1_101078_2023-02-15_final.stac-item
2023-03-03 10:26:07	ga_ls9c_ard_3-2-1_101078_2023-03-03_final.stac-item
2023-03-03 10:26:55	ga_ls9c_ard_3-2-1_101080_2023-03-03_final.stac-item
2023-03-19 10:26:49	ga_ls9c_ard_3-2-1_101080_2023-03-19_final.stac-item
2023-03-28 10:20:29	ga_ls9c_ard_3-2-1_100080_2023-03-28_final.stac-item
2023-03-28 10:21:41	ga_ls9c_ard_3-2-1_100083_2023-03-28_final.stac-item
2023-04-04 10:26:38	ga_ls9c_ard_3-2-1_101080_2023-04-04_final.stac-item
2023-04-11 10:29:10	ga_ls9c_ard_3-2-1_102071_2023-04-11_final.stac-item
2023-04-20 10:26:32	ga_ls9c_ard_3-2-1_101080_2023-04-20_final.stac-item
2023-04-27 10:29:03	ga_ls9c_ard_3-2-1_102071_2023-04-27_final.stac-item
2023-04-29 10:21:27	ga_ls9c_ard_3-2-1_100083_2023-04-29_final.stac-item
2023-05-06 10:26:20	ga_ls9c_ard_3-2-1_101080_2023-05-06_final.stac-item
2023-05-13 10:28:54	ga_ls9c_ard_3-2-1_102071_2023-05-13_final.stac-item
2023-05-15 10:21:18	ga_ls9c_ard_3-2-1_100083_2023-05-15_final.stac-item
2023-05-29 10:28:45	ga_ls9c_ard_3-2-1_102071_2023-05-29_final.stac-item
2023-05-31 10:21:10	ga_ls9c_ard_3-2-1_100083_2023-05-31_final.stac-item
2023-06-07 10:26:07	ga_ls9c_ard_3-2-1_101080_2023-06-07_final.stac-item
2023-07-02 10:21:11	ga_ls9c_ard_3-2-1_100083_2023-07-02_final.stac-item
2023-07-09 10:26:15	ga_ls9c_ard_3-2-1_101080_2023-07-09_final.stac-item
2023-08-10 10:25:39	ga_ls9c_ard_3-2-1_101078_2023-08-10_final.stac-item
2023-08-26 10:25:46	ga_ls9c_ard_3-2-1_101078_2023-08-26_final.stac-item
2023-09-04 10:19:40	ga_ls9c_ard_3-2-1_100078_2023-09-04_final.stac-item
2023-09-04 10:20:28	ga_ls9c_ard_3-2-1_100080_2023-09-04_final.stac-item
2023-09-11 10:25:56	ga_ls9c_ard_3-2-1_101078_2023-09-11_final.stac-item
2023-09-20 10:19:46	ga_ls9c_ard_3-2-1_100078_2023-09-20_final.stac-item
2023-09-27 10:25:53	ga_ls9c_ard_3-2-1_101078_2023-09-27_final.stac-item
2023-10-06 10:19:49	ga_ls9c_ard_3-2-1_100078_2023-10-06_final.stac-item
2023-10-13 10:26:05	ga_ls9c_ard_3-2-1_101078_2023-10-13_final.stac-item
2023-10-22 10:19:57	ga_ls9c_ard_3-2-1_100078_2023-10-22_final.stac-item
2023-10-29 10:26:04	ga_ls9c_ard_3-2-1_101078_2023-10-29_final.stac-item
2023-11-07 10:20:40	ga_ls9c_ard_3-2-1_100080_2023-11-07_final.stac-item
2023-11-14 10:26:03	ga_ls9c_ard_3-2-1_101078_2023-11-14_final.stac-item
2023-11-23 10:19:59	ga_ls9c_ard_3-2-1_100078_2023-11-23_final.stac-item
2023-11-30 10:26:11	ga_ls9c_ard_3-2-1_101078_2023-11-30_final.stac-item
2023-12-16 10:26:12	ga_ls9c_ard_3-2-1_101078_2023-12-16_final.stac-item
2023-12-25 10:20:03	ga_ls9c_ard_3-2-1_100078_2023-12-25_final.stac-item
2024-01-01 10:26:10	ga_ls9c_ard_3-2-1_101078_2024-01-01_final.stac-item
2024-01-10 10:20:46	ga_ls9c_ard_3-2-1_100080_2024-01-10_final.stac-item
2024-01-17 10:26:09	ga_ls9c_ard_3-2-1_101078_2024-01-17_final.stac-item
2024-01-26 10:20:44	ga_ls9c_ard_3-2-1_100080_2024-01-26_final.stac-item
2024-02-02 10:26:11	ga_ls9c_ard_3-2-1_101078_2024-02-02_final.stac-item
2024-02-11 10:20:00	ga_ls9c_ard_3-2-1_100078_2024-02-11_final.stac-item
2024-02-18 10:26:04	ga_ls9c_ard_3-2-1_101078_2024-02-18_final.stac-item
2024-03-05 10:26:04	ga_ls9c_ard_3-2-1_101078_2024-03-05_final.stac-item
2024-03-14 10:19:51	ga_ls9c_ard_3-2-1_100078_2024-03-14_final.stac-item
2024-03-21 10:26:01	ga_ls9c_ard_3-2-1_101078_2024-03-21_final.stac-item
2024-03-30 10:19:42	ga_ls9c_ard_3-2-1_100078_2024-03-30_final.stac-item
2024-04-06 10:25:52	ga_ls9c_ard_3-2-1_101078_2024-04-06_final.stac-item
2024-05-01 10:20:06	ga_ls9c_ard_3-2-1_100080_2024-05-01_final.stac-item
2024-05-01 10:21:18	ga_ls9c_ard_3-2-1_100083_2024-05-01_final.stac-item
2024-05-08 10:25:29	ga_ls9c_ard_3-2-1_101078_2024-05-08_final.stac-item
2024-05-17 10:21:10	ga_ls9c_ard_3-2-1_100083_2024-05-17_nrt.stac-item

Return to ga_ls9c_ard_3 whole collection overview

ga_ls9c_ard_3: Geoscience Australia Landsat 9 Operational Land Imager and Thermal Infra-Red Scanner Analysis Ready Data Collection 3

Baseline satellite data

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years